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With over 1800 students, INSAID continuously delivers quality Data Science education to budding Data Scientists all across India. 

Today, we are in conversation with INSAID’s Chief Operating Officer, Nikhil Bhogaraju, to see how INSAID classes achieve the best classroom environment, compete with global standards of learning and promise aspiring Data Leaders to flourish in their domain.

This is Part 2 of the conversation. To read Part 1, click here.

INSAID Data science classes

Malvika: Learning in online format means no face-to-face interaction. How do INSAID classes ensure students’ motivation levels are high throughout their program duration? 

Nikhil: Maintaining high motivation levels of students throughout the program duration is an extremely challenging task for any online program. The biggest challenge that we face is that, for example, whenever a user signs up for any program, in general, is that Day 1 it is like hitting a gym.

Day 1 your motivation levels are high, Day 2 they are high but by the time you touch week 1, your motivation levels go down because it is essentially an additional task that you have to allocate in your day-to-day routine, and you need to do it consistently to get some results out of it

So the way we have broken this elephant down is that we want to restrict INSAID classes only to weekends. Firstly, the professionals are comfortable and after office hours on weekdays, they’re not attending classes. They don’t have that kind of pressure of understanding something during that point of time. 

The second thing is that obviously during the weekdays they’d be having some assignments to do, some self-checks to evaluate how much they have understood and if they need to watch the recording again to understand or refresh the concepts.

Other than that on weekdays, we have different programs that we bring in, for example, on a monthly basis, we bring in top speakers who are very popular in the Data Science community.

They conduct sessions for our students. Basically in these sessions, the goal is that students should know the real-world applications as well while they’re learning. 

For example, we have brought someone who’s known as the Father of AI, Dr Kirk Borne. The goal is that while somebody is learning, at that very moment, they should know how this has been applied actually in practice so that they can relate more and they know what they’re signing up for. 

Another way of engagement is that we have started this new initiative called Fireside Chat with the mentors here at INSAID. This is also a monthly activity which very soon could be turned into a bi-weekly activity. 

The goal of this Fireside Chat is to keep up with the updates of what is happening in this industry. Staying updated is difficult for everyone because there are only 20-30% of students who are readers by nature in an entire batch.

If someone is not following blogs or not reading news about Data Science day in and day out, they will miss out on how fast the field is evolving and what kind of new trends are coming up, what changes are happening over a period of time and how career trend lines are changing. 

For example, the biggest myth people have is that Data Scientist is the ultimate position. You ask anyone who’s an aspirant for Data Science learning, he says that I want to become a Data Scientist, but there are 10 different positions that the person is actually eligible for but because he’s targeting exclusively a Data Scientist’s position, he is not being able to crack interviews. 

To solve this, we want to do sessions around these things where mentors are giving constant guidance and they’re having a live Q&A interaction with the students, which keeps the motivation levels high. 

One of the other things that we do is towards the second half of the program, say for example, you’re signed up in a 3-month program or in a 6-month program, usually towards the last terms of your program, we do this activity called our Data Science Career Launchpad

This is a series of 1-month workshops that happen every week, where the focus is towards building their entire Data Science portfolio. Everybody knows that their resume is not in the best shape but they slack thinking they will work on it when it is required and when I’m actually applying somewhere. 

By the time that situation comes, you do not have time to focus on your resume because resume preparation will easily take about 5-6 revisions to have it in perfect shape. When we do a week-long activity for that we believe that students actually take that time to dedicate to their resumes so we need to do it in a step-by-step way. 

The second week in INSAID classes is focused on LinkedIn. You need to build your profile and connections systematically. So that’s how we bring in different aspects, apart from learning to keep the motivation levels continuously high throughout the program. 

 

Malvika: Since you conduct the Data Science Career Launchpad sessions, can you discuss the underlying goals and objectives of the same (resume building and GitHub)? How important is it for students to attend our resume and GitHub INSAID classes? What do they stand to gain?

Nikhil: As we were discussing earlier as well, Data Science Career Launchpad is a 1-month activity in itself.

As I said, all the programs are outcome-based programs. So whatever are the logical outcomes that can be and in most cases people would want to transition into this field and want hikes and all, you cannot just simply say that I have done a program from XYZ place no matter what the place is, and say that I have a particular certification so that’s why I’m qualified for a particular job. 

Especially whenever you are attending a Data Science interview; an Analyst position or an Engineer position, or a Specialist position or a Data Scientist position itself, you need to have your entire portfolio ready. 

Your portfolio should highlight the kind of skill set you have, your thought process, your dashboarding skills, level of communication skills, and what is your past experience. All these variables are important and they’re considered. It is just not a new program that you have done and you’re expecting a result out of it. 

If we were one of those institutions where we are just focusing on the learning part and not the outcome, it would be easy to have people certified and say that now you’re eligible for jobs so start applying left, right and center. 

We’re not that kind of an institution, we need to bridge that gap because these are the exact same people who have signed up for a program to go step-by-step and learn something out of it. 

Now once you’ve learned whatever is taught but you’re not able to put it across outside where you actually stand to advantage from whether it be transition or upscaling, it’s a waste.

In the Launchpad sessions, first week we focus on resumes and like I said, resumes require 5-6 revisions at least. You just cannot build your 1-2 page resume at best in one go. 

Let’s suppose one day you will focus on the description part of it and another day you will focus on how you highlight your work experience.

I have seen people who apply to different positions and write down everything about their project, and it has like 10 bullet points for five different projects. This ends up making your CV like five pages long, but I’ll never make any sense about that.

There are no metrics. For example, people don’t talk about how many hours they worked on the project for, how much value that project is worth, and what kind of contribution they have done to that particular project. People always say that say I worked on so and so Project, used these tools one, implemented that but what are the outcomes? Why did you do it? 

These kinds of specifics and metrics are focused upon in these workshops. You learn in that week-long activity that how do you project yourself in a great way?

Say the second week at INSAID classes is focused on LinkedIn. Now I have seen students commit rookie mistakes by uploading their Facebook profile pictures on LinkedIn as well!

LinkedIn is a professional community and you need to look professional. Especially when you’ve signed up for a program which has a vision to groom Data Leaders. 

A Data Leader’s professional headshot cannot be a selfie of someone posing in the background of hills with 3-4 people around. Sorry to mention, some people just post their passport size photos as professional Display Pictures. 

So these kinds of corrections need to be done. Even students know that this needs to be done, it is just that they don’t allocate time to do it. We have adopted a step-by-step, structured process where we allocate a time for all of these tasks.

These things don’t impact majorly but subtly, somewhere or the other, all of these small points carry a big advantage whenever we are hiring people. 

Say the third week at INSAID classes is focused on the GitHub profile. While LinkedIn is your professional network where people get a summary of who you are, GitHub is the best place to show your skillset; for example, if you are a Developer, what kind of logic you’re applying and how well you are able to code is something nobody really gets to see that without GitHub.

It is not for the regular HR recruitment. but the Technical Hiring Managers who would interview your technical skills, would want to know what your thought process is and what kind of logic you have.

Your resume will not reflect that, your GitHub profile will show that. 

So we do a week-long activity based on that. An average person, for example, if you take a GCD program, will easily be doing 6-8 projects by the end of their program; one term project each and two capstone projects. 

On a bare minimum, they’ll do 8 projects and we’d want to position those 8 projects in the right way on their GitHub and they should distribute their GitHub whenever they’re going for a technical interview. 

The last part is Interview Grooming. In terms of interview grooming the challenge is that somebody has worked on their resume correctly, which has gotten them shortlisted.

Now, with their GitHub right in place, their chances of getting through to a technical interview is taken care of. Once you go to technical interviews, you need to be totally ready, the way you communicate also needs to be taken care of. This last week then comes into the picture, where students appear for mock interviews.

We reveal what kind of questions will be asked during the interview. Otherwise, most of the newbies who are going to the first couple of interviews will obviously fail in their interviews, and then not be able to figure out why. 

The why part is that say, I have learned a program, I have completed a particular project, you ask me anything about the project or about what I have learned and I will be able to explain it 100%. But the moment you introduce a new business scenario, and ask them to give an overlay of solutions or steps, I will take a backseat.

In most of the Data Science interviews, these are the kind of questions which will pop up. In terms of application, I have known one thing, but I don’t know what are the other ways of solving the same problem. 

So we just expose them to other ways of solving problems. We expose them to some of the best interviews that are being conducted, what kind of questions they should expect, and how should they prepare for an interview. 

We truly believe that this 1 month INSAID Career Launchpad is something that will bridge this gap. I’m not saying that it will be 100% effective but it will bridge 80% of the gap between learning and presentation.

Malvika: Thank You for taking out time for this Nikhil! This was a much-needed discussion for our students.

Author

Content Writer @ INSAID. A machine learning buff who loves to read, write and explain everything AI!

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